def create_timeseries_plot(recording):
out = CreateTimeseriesPlot.execute(recording_dir=recording['directory'],
channels=recording.get('channels', []),
jpg_out={
'ext': '.jpg'
}).outputs['jpg_out']
kb.saveFile(out)
return 'sha1://' + kb.computeFileSha1(out) + '/timeseries.jpg'
def create_waveforms_plot(recording, firings):
out = CreateWaveformsPlot.execute(recording_dir=recording['directory'],
channels=recording.get('channels', []),
units=recording.get('units_true', []),
firings=firings,
jpg_out={
'ext': '.jpg'
}).outputs['jpg_out']
kb.saveFile(out)
return 'sha1://' + kb.computeFileSha1(out) + '/waveforms.jpg'
def summarize_recording(recording):
ret = deepcopy(recording)
ret['computed_info'] = compute_recording_info(recording)
firings_true_path = recording['directory'] + '/firings_true.mda'
ret['plots'] = dict(timeseries=create_timeseries_plot(recording))
channels = recording.get('channels', None)
units = recording.get('units_true', None)
if kb.findFile(firings_true_path):
ret['firings_true'] = firings_true_path
ret['plots']['waveforms_true'] = create_waveforms_plot(
recording, ret['firings_true'])
true_units_info_fname = compute_units_info(
recording_dir=recording['directory'],
firings=firings_true_path,
return_format='filename',
channel_ids=channels,
unit_ids=units)
kb.saveFile(true_units_info_fname)
ret['true_units_info'] = 'sha1://' + kb.computeFileSha1(
true_units_info_fname) + '/true_units_info.json'
return ret
def create_waveforms_plot(dataset,firings):
out=CreateWaveformsPlot.execute(recording_dir=dataset['directory'],firings=firings,jpg_out={'ext':'.jpg'}).outputs['jpg_out']
kb.saveFile(out)
return 'sha1://'+kb.computeFileSha1(out)+'/waveforms.jpg'
def create_timeseries_plot(dataset):
out=CreateTimeseriesPlot.execute(recording_dir=dataset['directory'],jpg_out={'ext':'.jpg'}).outputs['jpg_out']
kb.saveFile(out)
return 'sha1://'+kb.computeFileSha1(out)+'/timeseries.jpg'
